The Future Of Software Engineering - NO MORE CODING

Summary

本视频探讨了软件工程的未来，指出随着GBT模型等AI技术的进步，传统的软件工程师角色将发生巨大变化。AI工具如Co-pilot提高了编码效率，而GBT应用构建器的出现预示着编程可能变得更加普及。未来，软件工程师可能更多地从事咨询、系统设计和维护AI工具等工作。视频强调了适应新技术、提升设计和领域知识的重要性，以保持在行业中的竞争力。

Takeaways

• 🚀 软件工程的未来将会发生巨大变化，目前所谓的软件工程师角色将很快变得不同。
• 🛠️ GBT 模型的最新改进以及宣布的 GBT 应用构建器预示着软件工程领域的剧变。
• 🔧 目前有许多工具正在提高软件工程生产力，例如代码自动完成工具 Copilot。
• 🔍 新工具专注于测试方面，帮助发现潜在漏洞并提供解决方案。
• 💡 随着 GBT 技术的发展，许多现有的软件工程技能可能会变得不再那么重要。
• 📈 未来软件工程可能会转向更多咨询型或系统设计和架构的高级角色。
• 🔑 软件工程师的工作重点将转向编写提示、描述和项目需求，而不是编写代码。
• 🤖 对于不想编写代码的人，可以完全依赖 GBT 技术或其他 AI 驱动的工具来构建应用。
• 🌟 AI 构建工具虽然还不是完美的，但已经是一个改变游戏规则的工具。
• 🏢 随着 AI 技术的发展，大型科技公司可能会考虑使用这些技术来减少软件工程师的开支。
• 📚 对于未来的软件工程师来说，专注于设计和深入了解领域知识将是关键，以避免被 AI 取代。

Q & A

未来软件工程将会如何改变？

未来软件工程将会因为GBT模型等AI技术的进步而发生巨大变化。这些技术将使得编程更加自动化，从而提高编程效率和水平。

GBT应用构建器是什么？

GBT应用构建器是一种基于GBT模型的工具，它允许用户通过自然语言描述来创建应用程序，而无需编写代码。

编程辅助工具如Co-pilot的作用是什么？

Co-pilot等编程辅助工具可以帮助程序员自动完成代码编写，提供建议和修复漏洞，从而提高编程的熟练度和生产力。

AI技术如何影响软件工程师的角色？

AI技术可能会使软件工程师的角色转向更多咨询和系统设计方面的工作，而不仅仅是编写代码。

未来软件工程师需要哪些技能？

未来的软件工程师需要具备深厚的设计能力、对工具的了解以及特定领域的知识，以便能够有效地使用和判断AI工具的输出。

GBT技术可能对软件工程行业产生哪些影响？

GBT技术可能会降低成为软件工程师的门槛，提高创新速度，并创造新的工作机会。同时，它也可能导致传统的编码工作变得不那么重要。

企业如何利用GBT技术降低成本？

企业可以通过使用GBT等AI工具来减少对软件工程师的依赖，从而降低开发成本。

目前GBT应用构建器的局限性是什么？

尽管GBT应用构建器是一个游戏改变者，但它目前还不完美，可能无法处理复杂任务，且生成的代码可能需要进一步优化和审查。

软件工程师如何应对AI技术的挑战？

软件工程师应该专注于提升设计能力、深入理解特定领域知识，并掌握最新的AI工具，以保持自己的竞争力。

AI技术在软件开发中的作用是什么？

AI技术可以自动化许多开发任务，如代码编写、测试、调试和文档生成，从而加快开发速度并提高产品质量。

软件工程师在AI时代的角色将如何转变？

软件工程师的角色可能会从直接编写代码转变为更多地监督和管理AI工具，确保它们按照预期工作，并保持代码的高质量标准。

Outlines

00:00

🚀 软件工程的未来与变革

本段落主要讨论了软件工程的未来趋势，强调了GBT模型等技术的进步将如何改变软件工程师的角色。提到了诸如Co-pilot这样的工具正在提高编码效率和质量，并且新的工具专注于测试和调试，帮助工程师发现漏洞和生成文档。同时，指出了GBT技术可能会使许多传统软件工程技能变得不那么重要，未来的软件工程师可能更多地从事咨询、系统设计和架构等高级角色。

05:01

🌟 技术进步对软件工程师的影响

这一段深入探讨了技术进步，特别是GBT应用构建器等工具的出现，将如何影响软件工程师的工作。强调了这些工具的发展可能会导致软件工程的门槛降低，使得更多人能够参与到软件开发中来。同时，讨论了这些变化可能会创造新的职业机会，但也可能导致某些软件工程角色的重要性下降。最后，提出了对于当前软件工程师的建议，即不仅要会写代码，还要掌握设计和领域知识，以保持竞争力。

Keywords

💡软件工程

软件工程是指使用工程原理、方法和工具来开发、维护和退役软件系统的一门学科。在视频中，软件工程的未来被讨论，特别是在GBT技术等人工智能工具的影响下，软件工程师的角色和工作方式可能会发生显著变化。

💡GBT模型

GBT模型可能是指一种基于人工智能的模型，用于软件开发和其他技术领域。在视频中，GBT模型的进步和宣布的GBT应用构建器预示着软件工程领域的重大变革。

💡代码自动完成

代码自动完成是一种工具或功能，可以在编程时自动预测并建议接下来要编写的代码片段。这种工具提高了编程的效率和生产力，因为它减少了手动编写代码的时间。

💡测试工具

测试工具是用于检查和验证软件应用程序的功能是否符合要求的软件。它们帮助发现潜在的漏洞和错误，确保软件产品的质量。

💡调试工具

调试工具是帮助程序员找到和修复代码中错误的软件。它们通常提供一系列功能，如断点设置、代码单步执行和变量检查，以便更好地理解程序的行为。

💡文档生成

文档生成是指自动创建软件文档的过程，这些文档可以包括用户手册、API文档或系统架构说明。这个过程可以节省大量时间，并确保文档的一致性和更新。

💡无代码

无代码是一种软件开发方法，它允许用户创建应用程序而无需编写代码。这种方法通过使用图形界面和预构建的模块简化了开发过程，使得非技术背景的人也能参与到软件开发中来。

💡提示驱动开发

提示驱动开发是指通过向人工智能工具提供描述性提示或项目需求，让工具根据这些输入自动生成代码或其他开发成果的方法。这种方法强调了与工具的交互和指导，而不是手动编写每一行代码。

💡系统设计

系统设计是指规划和构建复杂系统的过程，包括确定系统的结构、组件、接口和其他特性。在软件开发中，系统设计是创建高效、可靠和可维护系统的关键步骤。

💡领域知识

领域知识是指在特定学科或领域内具有的专业知识。在软件开发中，领域知识可以帮助工程师更好地理解问题，选择合适的工具和技术，以及做出更明智的决策。

💡AI工具开发

AI工具开发是指创建和维护利用人工智能技术的工具和应用程序的过程。这些工具可以用于各种目的，如自动化任务、数据分析和软件开发。

Highlights

未来软件工程的发展将会与今天大不相同

GBT模型的最新改进和GBT应用构建器的宣布将带来软件工程领域的剧变

目前有许多工具正在提高软件工程的生产力，例如代码自动完成工具Co-pilot

新的工具专注于测试方面，帮助发现漏洞并提供解决方案

软件工程的工具正在帮助工程师进行调试和生成文档

GBT技术可能会使许多现有的软件工程技术变得不再相关

软件工程领域的准入门槛看似降低，但实际上要成为一名优秀的开发者仍然不易

随着GBT等AI工具的强大，软件开发的编码方面将变得更加易于接触

未来软件工程师的工作重点可能会转向编写提示、描述和项目需求

GBT技术可能使软件工程师的角色转变为更多咨询和系统设计方面的工作

新的软件工程角色将专注于设计和维护AI工具

开发者需要编写工具来实现完全替代编码的目标

尽管GBT应用构建器还不是完美的，但它已经是一个游戏规则改变者

大公司可能会考虑通过利用这些技术来减少软件工程师的开支

目前我们正处于软件开发的早期阶段，但正在从初步探索转向实际应用

GBT技术可能在不久的将来帮助我们无需编码背景就能构建工具

软件工程师的最大资产不应该是编码能力，而应该是设计和知识

为了不被AI取代，人们应该专注于构建深度和真正了解自己擅长的领域

Transcripts

hey guys welcome back Luca here today I

want to talk about the future of

software engineering and how what we

know today as a software engineer will

soon be very different there has been a

lot of recent improvements on what the

gbt model can do and they also announced

a gbt app builder so very soon we'll see

a dramatic change in what we know as

self engineering one lately we've been

seeing a lot of tools that improves

software engineering productivity tools

such as co-pilot where while we are

writing code they help us autocomplete

or tell us hey this is something that

you should consider writing these type

of tools are being developed right now

and it's helping to increase coding

proficiency and productivity levels

there are new tools that focus on the

testing aspect trying to see like oh

here are some vulnerabilities and this

is something that we can do like as a

software engineer on tools that help

engineer debug and trying to apply fixes

or generate documentations but with this

gbt Technologies like a lot of these

might become more irrelevant and now we

are heading towards more of a second

phase of where soft engineering is

heading towards like to many people are

surprised sure like software engineering

was considered something that oh we can

easily pivot into there were many ways

for people to Pivot into s engineer such

as joining a boot camp study computer

science on their own doing personal

projects so it seems like oh yeah the

entrance of barrier isn't as high but we

all know like you know it is still

pretty high to become a good enough

developer and that was something that

was making this feel very lucrative but

with this recent development that's way

more powerful than the no code

alternative that we currently have today

is going to make self engineering coding

aspects way more accessible for a lot

more people I think based on the demo

like we can pretty confidently say like

Yeah The Future Is Almost Here we are

about to head in towards a prompt driven

development this is how I would describe

it where we won't be spending as much

time writing code where we will be

spending a lot of times writing prompts

writing descriptions writing project

requirements telling the tool to come up

with something and as a softare engineer

your main focus on the job will just be

trying to see like oh does the code

right in a good style or does it make

sense but if you're someone who don't

even want to worry about coding then you

can trust fully on these gbt

Technologies or whatever AI power tool

to help you build whatever app you

desire simply use natural language and

describe what the feature is about you

will be followed through a prompt that

guides you how how to build your app and

this is something that's really powerful

and it's going to really ship the

dynamic of software engineering so this

will definitely speed up the pace of

innovation creates new opportunities but

it might also make software engineering

not as relevant so if you are someone

who's now in Tech and you are building a

new app now you get to decide if you

trust the gbt technology fully or you

want to hire a software engineering

figure or someone who knows software

engineering and trying to hold the

quality bar of the product you might

still have access to the code you don't

know coding but you don't know how well

it's written there might be

vulnerability or not do you trust the AI

generator tool fully completely or you

want to hire someone who might be a

consultant

figure so I feel like self engineering

will definitely become more of a

Consulting type of role or some sort of

system design architectural like senior

level type of roles so as a self

engineer in the future your job might

look very different from what you

currently do you might have more

requirement on designing and being very

specific about the type of system you

want to know so this actually require

you to know a lot about the domain the

type of tools available out there

because you need to be able to judge

like oh does this two make sense does

this make sense like do I go with

database type A or do I go with database

type B like or do I blindly just

completely trust what the GPT think is

the best at the moment but we don't know

if the gbt tool will be as powerful just

yet so you still have to be the type of

decision makers and provide as much

relevant information as possible cuz

maybe lacking a bullet point a might

lead to a complete different result and

that result may not be what you want so

it's very tricky in the aspect so I do

think because of this like new roles

will be created that's focusing on

design and focusing on developing and

maintaining these type of AI tools and

to start off you also need to have

people who are building these products

in the first place so before you can

fully replace coding you have to have

developers who can help you write these

tools to make it happen and I do think

we are getting closer and closer like

right now the open a I a builder tool

isn't perfect but it's definitely a game

changer and I know for a fact a lot big

more bigger companies will be eyeing

this and trying to focus on it given

that software engineer are one of the

biggest expense for a lot of bigger tech

companies they might look into reducing

this expense by leveraging some of these

Technologies and they definitely putting

in a lot of money into developing these

type of tools so right now we are still

at the early stage but we are definitely

pivoting from oh this is the buds like

we finally got J AI this is what it can

do too okay this is looking a little

scary this is getting to a point where

we could actually rely on them to help

us build start a build tools without

even having to know any coding

backgrounds it's not perfect the code it

writes may not be perfect but the fact

that it can go from zero to 100 in

matters of minutes hours like based on

how you describe your task it's

tremendous like it's going to take

software engineer month to maybe even

build a product to have the speed of a

turnaround but now you can rely on gbt

to go from zero to 100 really fast of

course scaling it right now is going to

be tricky for sure for this gp2 to

handle which is why you might still need

expert you might need the software

engineer in that aspect but besides that

yeah it looks like it's going into a

really solid position so why I saw the

news I was first impressed and then I

definitely also felt like wow it feels

like it can do my job almost as well as

I can that's why I say if you are a self

engineer your biggest asset shouldn't be

the fact that you can write code that

should be a default you should try to

build something on top of that that

separates you is it the the type of

design is it the type of pattern use is

the knowledge because you may never

write as fast as the AI so purely going

for Speed shouldn't be the focus so for

people who are thinking about starting

that would be my recommendation like you

should try to build a lot of depths and

trying to really know the stuff that you

do well and this will prevent you from

being replaced by AI at least in the

first phase if we do get to that point

in the near future so yeah guys thank

you so much for watching and I hope you

guys enjoyed this video make sure to

like comment and subscribe I will see

you guys next

time